fitnessDistanceBalance.m

function index = fitnessDistanceBalance( population, fitness )

[~, bestIndex] = min(fitness); 
best = population(bestIndex, :);
[populationSize, dimension] = size(population);

distances = zeros(1, populationSize); 
normFitness = zeros(1, populationSize); 
normDistances = zeros(1, populationSize); 
divDistances = zeros(1, populationSize); 

if min(fitness) == max(fitness)
    
    index = randi(populationSize);
    
else
    
    for i = 1 : populationSize
        value = 0;
        for j = 1 : dimension
            value = value + abs(best(j) - population(i, j));
        end
        distances(i) = value;
    end

    minFitness = min(fitness); maxMinFitness = max(fitness) - minFitness;
    minDistance = min(distances); maxMinDistance = max(distances) - minDistance;

    for i = 1 : populationSize
        normFitness(i) = 1 - ((fitness(i) - minFitness) / maxMinFitness);
        normDistances(i) = (distances(i) - minDistance) / maxMinDistance;
        divDistances(i) = normFitness(i) + normDistances(i);
    end

    [~, index] = max(divDistances);

end

end